What if SQL queries could process data as it is generated instead of after it is stored? Apache Flink speaks SQL fluently, but it is not a database – it is best understood as a conductor orchestrating endless streams of data rather than a librarian managing stored records.This session bridges the gap between traditional SQL and stream processing.In this session, Viktor Gamov will explore:The mental model shift: from “querying the database” to “continuously processing the stream,” using intuitive analogies Flink SQL in action: how familiar operations like SELECT, JOIN, and GROUP BY work on infinite data streams, plus temporal joins, time windows, and watermarks Table API: programmatic control with declarative simplicity, bridging SQL and full programming flexibility Flink AI: real-time feature engineering and model inference on streaming data using SQL-like patterns Real-world patterns: fraud detection during transactions, live analytics dashboards, and event-driven architecturesAttendees will leave understanding not just how to use Flink SQL, but also when and why it transforms traditional database skills into real-time data superpowers.This session is ideal for SQL developers and data engineers ready to make their queries travel through time.